In the previous section, we described three different ontological foundations: determinist, aggregation/reductionist, and reflexive. The next step is to establish how a commitment to one of those three ontological foundations influences how we develop scientific knowledge from each of these ontologies. Returning to our code metaphor, we can think of our ontology as a language we select to write our code and develop scientific programming. Some computer languages are better suited for the development of software that runs video games, while other languages are best applied in web design or budgeting software. A similar situation exists for our ontological foundation. As we examine the related epistemologies, we question the ontological grounding and thus develop new methodologies for addressing our scientific inquiries. This is an important exercise to undertake. Revisiting and assessing our foundation protects us from spending too much time trying to fix bugs in a program that can never really be resolved without changing the language we are operating from. Or as Albert Einstein once argued with explicit reference to the concepts of time and space: “It is necessary over and over again to engage in the critique of fundamental concepts, in order that we may not unconsciously be ruled by them”.

One such challenge to fundamentals arose during the Enlightenment. Challenging the knowledge claims being made by the church to sustain the social structure of the feudal era, Francis Bacon, and others began the process of developing science as an alternative method for knowledge creation. Under the determinist ontological paradigm, knowledge was derived and shared via the church and the priests who interpreted the word of God for the people. One can imagine this mode of understanding the world as being limited. Without a defined epistemology, myth, legend, and superstition dominate narratives about how the world works. Consequently, years and at times centuries have been defined by ideas like the world is flat, diseases are caused by black bile in our blood, and women who questioned conventions about gender roles or other social norms were vilified as evil and witches. Such a world is not one open to critical thinking, experimentation, or capable of much more than the smallest increments of social change.

This all, however, did begin to change. Global trade, the discovery of bacteria, and new notions of freedom and individuality all challenged feudalism’s repressive ontological order and its conventions. Such challenges are what Thomas Kuhn called anomalies. Kuhn’s 1970 The Structure of Scientific Revolutions was specifically analyzing science and not convention grounded by religion; this framework for thinking about paradigm shifts is applicable. In short, Kuhn’s argument can be described as a process where anomalies or findings that contradict the existing system of knowledge claims, i.e. the world is not flat, or people do not have black bile in their bodies, encourage people to seek new methods for understanding the world around them. New approaches to understanding the world yield better or more reliable explanations like the sun is the center of our universe. These discoveries usher in a new paradigm and a  generally accepted set of methodologies emerge and replace the previous system of knowledge creation.

One significant contribution to Western thought’s transition occurred when Sir Issac Newton  returned home from his studies at Cambridge, while Europe contended with the bubonic plague epidemic in 1665. It was during this 17th-century “stay-at-home mandate” that Newton observed (as the legend is told) an apple falling from a tree and inquired why it fell in a straight line, rather than at an angle or even up. From this inquiry, Newton was able to show that the force that makes the apple fall and keeps all of us from floating away is the same force that maintains the orbits of the moon and the planets. The body of scientific inquiry or academic discipline that originates from Newton’s studies is Physics.

Specifically, in Newton’s 1687 Philosophiae Naturalis Principia Mathematica (Mathematical Principles of Natural Philosophy), he applies the universal law of gravity to formalize methods for studying, among other things, rates of change, velocity, inertia, and all sorts of physical relationships in the natural world. While many of you might like to live in a world without calculus, Newton’s work made the application of mathematical differentiation and integration primary tools for understanding how many of the things in our world work.

The universality of the law of gravity sparked great interest in the discovery of other such universals and unleashed a new paradigm of scientific inquiry.  Astronomy, chemistry, agriculture, medicine, and evolutionary biology all experienced exponential leaps forward as empirical analysis, the scientific method, and new techniques for predicting cause-and-effect relationships displaced religion and mythology as primary explanations of reality. A reality that can be known and studied by anyone, rather than just communicated to us through the church. The scientific method opened up a reality that humans discover by breaking apart and explaining all of the building blocks of life.

Starting from an ontology of the whole is equal to the sum of its parts, the corresponding revolution in science shifts, not only knowledge and science but unleashes political, social, and cultural change as well. Such changes in the dynamics of society raise questions about how best to understand and study the dynamics of social change. For many, the answer was right there in front of them. Why not use the theories of knowledge creation that are yielding such amazing results in fields like astronomy and physics? Why not use the tools and methodologies of the natural sciences to explain our social systems?

Positivism and Neoclassical Economics

The idea that we can use tools from the physical sciences to model and understand human activity is a compelling one. As we noted earlier, the Positivist paradigm is based on that idea.  Positivism, as a scientific philosophy, argues for the use of physical science principles like rates of change and velocities are valid and useful techniques for addressing social science inquiries. Application of these mathematical tools can be used to investigate the nature and causes of price movements or fluctuations in the business cycle, for instance.

Economists in the late 19th century set out to establish just such an explanation for the economy. Grounded by the ontology that the whole or the economy was simply the sum of its parts. Neoclassical economics emerges as a project to merge Adam Smith’s understanding of the butcher, the baker, and the brewer, and the classical political economy of the industrial revolution with the rigors of Newtonian physics. From this project, a new mathematical and rhetorical language for the economy is created. Words like optimal, rational, efficient, equilibrium, and the “forces” of supply and demand remain relevant today, as people use the conventions of economics to explain phenomena such as inflation, recessions, and poverty.

Neoclassical economics is the bedrock of orthodox economics. Orthodox economics, as stated earlier in this chapter, is the study of the allocation of scarce resources among competing ends. The orthodox definition is grounded by the aggregation ontology. This foundation positions the economy as an observable phenomenon that can be studied and modeled using mathematical tools that describe rates of change, velocities, and equilibrium conditions. These same tools are used for a variety of tasks across multiple disciplinary studies. A sampling of these tasks includes tracking planetary orbits, landing the lunar module, and building suspension bridges. In economics, these tools require analogs for cells and atoms to function as the individual or smallest component parts. In addition, economists also require a universal law to anchor their models the way gravity does for astronomy or engineering.

One of the earliest and most well-known successes in utilizing the tools of mathematics to establish an economic law was accomplished by Sir Alfred Marshall in his 1890 Principles of Economics. In this famous text, Marshall derives the demand curve with the very tools you will apply in this textbook. From this derivation, Marshallian Demand and the law of demand emerged as a cornerstone of neoclassical economics and orthodox economics in general. The law of demand states that when prices go up people consume less and vice versa. As we will see, Marshall derives the demand curve from the aggregation of optimal choices. This aggregation yields the structure commonly referred to as the demand curve. The demand curve is the sum of its parts. To allow for the summation of optimal consumer choices, several significant assumptions must be made about how consumers make those choices.

Assumptions are an essential element of economic models. To model the abstract conceptualization of how consumers make choices based on their incomes and the prices they face, the orthodox economics utilizes constrained optimization. Constrained optimization is the process of finding the maximum or minimum of an objective function with respect to unknown variables in the presence of a constraint. The objective function in consumer theory is the utility function. This function describes how consumers derive satisfaction or utility from their consumption.  In this text, we will almost exclusively limit constrained optimization to two unknown variables. These two variables will be modeled by x and y in the Cartesian plane. The optimal point will be the maximum or minimum that solves the allocation of resources given the constraint the consumer or producer faces. The consumer optimization problem can be written in plain English, mathematically, and described in a two-dimensional diagram. This will be true of almost all of our models in this text.

To utilize constrained optimization for economic analysis, we must fit the consumer into the mathematics. If individual consumers behave like a mathematical function, then these tools are appropriate for studying the economics of consumption. Assessing the validity of the assumptions about consumers and later firms as well as markets is an important task ahead. For now, we will limit the discussion to neoclassical consumption theory with a brief introduction to the model.

Constrained optimization is a process of solving for unknown variables that optimize the relationship between an objective and a constraint. The objective function in the consumer optimization problem is the utility function. This function is used to describe the consumer’s preferences and how much satisfaction or utility they achieve based on the basket of goods they consume. The consumer’s objective is to maximize their satisfaction, despite what Mic Jagger might say.

In order to describe the consumer’s objective mathematically, the functional form of the utility function generally meets these three basic assumptions.

1. Consumer preferences are complete. This means that a consumer can rank order all of the potential consumption baskets from most preferred to least preferred and identify those to which they are indifferent. Indifferent simply means they are equally satisfied by two baskets. For example, I might be indifferent between a basket with 4 cheeseburgers and 2 tacos and another with 2 cheeseburgers and 4 tacos.
2. Consumer preferences have transversality if X is preferred to Y and Y is preferred to Z, then X is preferred to Z. You try now with tacos, cheeseburgers, and pho.
3. More is always better than less.

Aside from the utilization of self-interest as the economists’ proxy for gravity, these assumptions do not sound all that outrageous. One could make the argument that they represent a fair number of individuals. This is desirable. If the model only fits one consumer, then it is not going to be able to tell us much about the economy. However, if the model fits a very large number of consumers, say every consumer that has ever lived, then the model tells us a great deal about the economy. So while these assumptions are based on a specific functional form, it does seem to be a terrible abstraction of the typical consumer. Exactly how this connects to mathematics will become clearer as we add the other components to our model of consumer choice.

The second component of our constrained optimization problem is the constraint. What constrains a consumer? Consumers are constrained by their income and the prices they face in the market. John Maynard Keynes argued in his book The General Theory of Employment, Interest, and Money that “man wants the moon.” By this, he was arguing, in a consistent fashion with the third consumer assumption about preferences, that human wants are insatiable. So to model behavior that is constrained, we add the budget constraint and take the moon out of the equation. In this text, the budget constraint is a simple linear function. The primary assumption about how the budget is utilized is that the consumer always uses every bit of their income to maximize their utility.

Now, this assumption might raise some eyebrows, because one of the founding fathers of the United States and scientist Benjamin Franklin told us that a penny saved is a penny earned. So should we be modeling consumer behavior with a mathematical model that assumes consumers spend every penny? There are a couple of ways to approach this. First, many Americans do live paycheck to paycheck, and many more live beyond their means using debt instruments like student loans, mortgages, and credit cards. These lived experiences indicate that from a real-world perspective, this assumption is not all that unrealistic. Another more technical way orthodox economists justify this claim is by arguing that savings are just future consumption. This line of thinking is modeled in a variety of modifications to the simple model we use in this text to think about consumer behavior in the face of inflation, for instance.

But for now, we will just stick with the simple idea that we spend all of our income to achieve maximum satisfaction. Therefore our mathematical abstraction, the constrained optimization model of consumer choice looks like this:

Max u(X,Y)

Subject to P_xX + P_yY = I

Relax, we will not go through the math to solve for the amount of X and the amount of Y that solves this problem (that will come later), we simply want to point out that the solution to this problem is a (x, y) coordinate in the cartesian plane. And, if we want to find the consumer’s demand curve, we can solve this problem many times by varying the price of one of the goods holding everything else constant otherwise known as ceteris paribus. The resulting collection of those optimal points can be pieced together in a price and quantity coordinate plane to build our demand curve. From this individual construction, we can further aggregate each individual demand curve to form a market demand curve.

This is made possible through aggregation. Therefore, the assumptions we make concerning how consumers make choices make them all identical. An optimal basket is an optimal basket or a point is a point just like an apple is an apple and we all know you can add apples to apples, but not oranges to apples.

So let’s briefly summarize. The ontological foundation of aggregation and ‘the whole is equal to the sum of its parts’ grounds orthodox economics. The selection of this ontology is made in large part because it allows the orthodox economist to use the tools of the natural sciences, specifically constrained optimization to model consumer behavior. This epistemological commitment to positivism makes the process of consumer choice identical across all consumers, separates the economy into a mathematical or control space for experimentation, and establishes a framework for deriving economic laws. Thus, orthodox economics studies the allocation of scarce resources among competing ends, by defining choice and our constraints to fit mathematical models. Results from such modelings, like the law of demand, are used by economists to forecast or predict how consumer demand for goods and services changes in response to changes in prices. This is similar to a baseball scout wanting to know how a pitcher’s velocity might change if they move from an indoor to an outdoor stadium.

The orthodox methodological approach to studying the economy is well-established and represents the dominant school of thought in the discipline.  Legos might provide a helpful example. The model we just constructed is the base model from which orthodox economics remains connected. However, the field has moved well beyond the simple two-dimensional utility function and the linear budget constraint. The pieces of the model are now much more complicated and elaborate. Visually Figure 3 displays this transition, from the Duplo basic building blocks to the more complex Lego sets capable of modeling Star Wars spaceships, like the Millennium Falcon.

Can Economists Learn from Cancer?

The use of the same mathematics that drives disciplines like engineering and astronomy affords orthodox economics a strong scientific veneer. The primary question to keep in mind as we proceed is if in fact humans are accurately modeled by these tools  . Such a question was raised by Albert Einstein:

It might appear that there are no methodological differences between astronomy and economics: scientists in both fields attempt to discover laws of general acceptability for a circumscribed group of phenomena in order to make the interconnection of these phenomena as clearly understandable as possible. But in reality, such methodological differences do exist (Einstein 1968: 11).

At first glance, this quotation appears to be principally concerned with epistemology, but Einstein is raising an ontological question. While it is intriguing to draw from the tools of the natural sciences to understand social phenomena like the economy, many scholars question the appropriateness of tools designed to study the solar system for understanding human activities. Thus, social science includes a vast array of disciplines that use and develop new methodological tools that study a reflexive ontology. When the whole is greater than the sum of its parts, the relationships and interconnections between agents and structures become the focus of analysis rather than the agents themselves.

An example of such a scientific transition might clarify. Unfortunately, many of us have either experienced or had a family member diagnosed with cancer. Oncology (not to be confused with ontology) is the study of cancer. Oncology has gone through multiple paradigm shifts. An early paradigm shift began with the transition in the theory of disease from black bile to an understanding of bacteria and the organization of human anatomy. This led to a series of projects to break down the human body into its smallest component parts. A cellular understanding of human biology has yielded extraordinary findings but also led doctors down paths that have not been as successful. In oncology, specifically, misunderstandings about how cancer moves and appears in the body led to decades of over-invasive surgeries and extreme chemotherapy dosages . However, continuous anomalies in treatment outcomes found using reductionist epistemologies led doctors and scientists to discover new answers that embrace a reflexive understanding of cancer and invent new treatments.

One might say these anomalies moved oncology out of the lab and into the world of social science. To answer questions about cancer’s spread, emergence, and return in some individuals, doctors needed to learn about their environments. Environmental health, in general, is in the midst of a renaissance that is actively seeking to understand how the spaces we occupy relate to cancer’s appearance in our bodies. This outside-of-the-lab environmental approach is also contributing to the development of methods that prevent diseases in the first place, by changing not just individual behaviors but also the environments in which we live our lives. Smoking laws are a prime example of how knowledge about environments or the structures we occupy can be changed by individuals and also alter the future health and well-being of those individuals or agents.

Cancer and the study of cancer is a strong example of a reflexive ontology for a couple of reasons. The first is that it brings into question the separation between the object of study and the researcher, what we have defined as duality. It does this by highlighting the necessity of understanding the cultural and social context of phenomena that are traditionally confined to the natural sciences, such as cancer. As such, the division between what we consider to be natural versus what is social becomes blurred and calls forth the need to understand the dynamics between structures and agents.

Additionally, oncology is advancing treatments for disease by understanding not just the cancer cell, but how cancer cells emerge as mutations of healthy cells based on a multitude of environmental factors. These factors range from microscopic changes in our blood, to whether or not someone decides to smoke, or is born in a particular neighborhood. Therefore, cancer can be treated through preventive measures, and through therapeutic interventions that are increasingly targeted and with much greater consideration given to the side effects the patient experiences during those treatments.

All of this is to say that economists could learn from oncology. Some economists take these lessons to heart and are actively pursuing methodologies that help us to understand the relationships between economic agents and the structures they produce and reproduce. Such a process is called a going concern and will be more carefully described in Chapters “Macroeconomic Viability and the Corn Model” and “Costing and Pricing in Going Concerns” . Until then, it suffices to continue to use institutions as a primary socially constructed unit of production and collective human activity. We will refer to economists advancing from a reflexive ontology as heterodox economists.

Heterodox Epistemologies

Heterodox economics is the study of social provisioning, in which an understanding of the development of political economies is rooted in social, political, natural, and cultural processes. Notice the differences between the two definitions. It is as though they are completely different areas of study. This is because each of these schools of thought is approaching the study of the economy from a different ontological foundation, as such their tools or methodological approaches are going to be very different. Just as the oncologist used one ontological foundation to justify radically invasive surgeries to prevent the recurrence of cancer, investigating the disease from a new ontology opened the possibility for new less invasive treatments, as well as the exploration of preventive measures.

Other differences in the definitions are more subtle. For instance, the orthodox definition emphasizes scarcity. In the heterodox definition, the emphasis is on the social provisioning process. The heterodox definition does not assume scarcity is an underlying human condition. For instance, institutional economist Thomas R. De Gregori, following in the footsteps of Clarence Ayers and Erich Zimmerman, argued “Resources are not, they become.”

The second big difference is that there is no assumption that competitive ends are the means by which resources are allocated. Heterodox economics opens up the possibility that people and institutions do not necessarily organize allocation along competitive lines. If we are to look around at various institutions and going concerns, we see that not-for-profits, unions, and even a sports league like the NFL all incorporate various concepts to promote coordinated cooperation, such as, democracy, revenue-sharing agreements, and collective bargaining. Looking at how different institutions interact and organize their workforce is one of many potential points of entry for examining the social provisioning process.

Finally, the heterodox definition includes social, political, environmental, and cultural processes as fundamental elements for understanding how the economy and thus the social provisioning process is animated. This is very different from the orthodox model that attempts to create a vacuum-sealed or controlled space for conducting economic analysis with their models and the assumptions necessary to make those models logically consistent. Remember, being able to separate the economy from politics, culture, and environment is related to the concept of duality. A clear example of this is the orthodox claim that the government or state intervenes in markets. This from a heterodox perspective is nonsensical as markets are socially constructed institutions that are embedded in society and an outcome of socially organized laws and institutions like property rights.

Therefore, the methodological tools applied by heterodox economists are very different from the constrained optimization and equilibrium thinking that dominate orthodox economics. While heterodox economists largely reject Newtonian physics as a valid model for understanding the economy, it is not the case that they reject mathematics or other natural science methods as productive tools for generating economic knowledge. For instance, the Corn Model in Chapter “Macroeconomic Viability and the Corn Model“, uses matrix algebra to model a simple system of reproduction using two inputs. This mathematical model provides insights into the operations of a going concern or business enterprise at a microeconomic level, and the late Dr. Frederic S. Lee  has shown that this tool is also capable of tackling questions and analysis of the economy as a whole.

Heterodox economists also employ tools developed in other social science disciplines, such as network analysis tools, spatial analysis techniques from geography, historical studies, case study analysis, ecological models, and critical legal studies. These represent a small sampling of how heterodox economists attempt to understand the social provisioning process from the social, political, and environmental context from which it is animated. While this multifaceted approach has some clear advantages in terms of realism and providing detailed explanations of various social provisioning processes, it does not allow heterodox economists to make as general or as bold a claim to scientific discovery as those made by the orthodoxy.

Remember the Law of Demand? This law is grounded by the idea that self-interested behavior operates on economic systems in the same way that gravity operates on our jump shot in basketball. In other words, claiming self-interest is as universal as gravity allows orthodox economists to make universal claims about economic behavior by both consumers and producers. These claims translate to a perception that market outcomes are somehow natural or beyond the control of human beings. So it becomes very important to understand the underlying assumptions of these arguments so that we do not stop innovation from occurring–innovation that could one-day end poverty or stabilize inflation without creating pain and hardship in communities through higher levels of unemployment.

Summary of Epistemologies

In sum, once we have made a decision about our ontology, we make a set of tools available for studying the economy and generating knowledge about that economic reality. From the orthodox perspective, the use of tools that have generated great knowledge and success in different disciplines in the natural sciences is attractive. Constrained optimization, rates of change, and equilibrium analysis help astronomers and engineers launch rockets and build bridges, so why wouldn’t that success translate into the study of our economy?

Heterodox economists reply by arguing that human beings and their institutions are not as predictable or reducible as the combustion of fuel or the movements of planets because there is no universal law that applies to their economic decisions. Instead, new techniques and methodologies need to be developed to understand how humans behave and provision their needs and wants in the social, political, environmental, and cultural contexts within which they occur. The economy cannot be studied in a vacuum or in a controlled environment. It is an open and ever-evolving system of interlocking and reflexive relationships.

This brings us to our final meta-theoretical consideration: our axiology or theory of value. Where does value come from and what determines value? It should come as no surprise that the answer you get is dependent upon that individual’s ontological and epistemological commitments.